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Author:

Wang, D. (Wang, D..) | Li, X. (Li, X..) | Zhao, M. (Zhao, M..) | Qiao, J. (Qiao, J..)

Indexed by:

EI Scopus SCIE

Abstract:

The wastewater treatment process (WWTP) is of great significance to environmental protection. To improve the efficiency of the WWTP, it is crucial to ensure that the dissolved oxygen (DO) concentration tracks the set value efficiently. Due to the nonlinear and time-varying dynamics of the WWTP, traditional control methods cannot accurately control the DO concentration. To overcome these challenges, this paper proposes an online transferred heuristic dynamic programming (TrHDP) control design by combining transfer learning with adaptive critic design. First, we use the historical sample data to construct a mathematical model of the WWTP and learn the prior knowledge from the model. Then, the online control process of the DO concentration is guided by utilizing the prior knowledge. In order to avoid negative transfer and save computing resources, we design a novel decay function with the truncation mechanism. In addition, we prove the stability of the TrHDP control scheme by constructing a Lyapunov function. Finally, the performance of the TrHDP scheme is verified by the Benchmark Simulation Model No. 1. Compared with other methods, the TrHDP method possesses higher control accuracy for the DO concentration and overcomes the disadvantage of low learning efficiency of general online methods. IEEE

Keyword:

Informatics Reinforcement learning Transfer learning Task analysis reinforcement learning Wastewater treatment Dynamic programming neural networks transfer learning Adaptive dynamic programming Trajectory wastewater treatment applications

Author Community:

  • [ 1 ] [Wang D.]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Li X.]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Zhao M.]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Qiao J.]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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Source :

IEEE Transactions on Industrial Informatics

ISSN: 1551-3203

Year: 2023

Issue: 2

Volume: 20

Page: 1-10

1 2 . 3 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:19

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 38

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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